Team Participants

Kristen Salathiel, Director of the Center for Instructional Excellence

Stephen N. Siciliano, Vice President for Educational Services

Rationale for Nomination

The purpose of the Perceptual Learning Method/Module is to introduce and reinforce concepts, ideas, or meaning without detailed explanation –or “any” explanation for that matter. The aim is to SHOW learners a concept, idea, or meaning and allow them to experience, see, and learn what IT is.

Largely inspired by chapter nine of How We Learn by Benedict Carey and backed by research and trials in Tom’s courses, the Perceptual Learning Method/Module (PLM) is a way of “learning without thinking” according to Carey. By rapidly working thru a series of images, learners receive feedback with every image they encounter. After approximately 50 minutes, significant perceptual learning will have occurred. What makes this different from flash cards is that rather than a one-to-one association, PLMs have a one-to-many association.

For example, in a PLM for Geography, rather than simply connecting an image of Albania to the correct answer “Albania”, the PLM would include images of Albania in different contexts—up close, from space, by itself, in the context of surrounding countries, etc. These images would cycle through the module randomly and the learner would be required to correctly associate them to the correct answer of “Albania” each time. All the while, random images of Macedonia, Croatia, Serbia, etc. would be cycling through the module and must also be associated with correct answers. Imagine the many applications for Political Science; Sociology, History, Art History, Biology, Surgical Technology, Automotive Technology, Physics, Nursing, Chemistry, various forms of corporate learning–any form of learning in which visual learning is ideal.

While built for use at Northwestern Michigan College, the PLM generator could have application in any type of training which requires that learners visually identify items. It is probable that any age group with dexterity enough to make selections on a computer keyboard would stand to benefit from this tool. Learning to generate PLMs is appropriate and accessible to all audience levels–beginner through expert.

In How We Learn, Carey describes his own learning experience using a PLM to identify various schools of artistic painting styles (without prior knowledge) and achieving 80% accuracy. He also detailed a case in which fledgling ground school students used a PLM to simulate zero visibility flight (night or fog) as indicated by various indicator dials. These ground school students then performed as well as experienced pilots with 1,000 hours of flight time. In both cases, Carey and the ground school students each invested only 50 minutes. Carey expresses his opinion at the end of the chapter that perceptual learning will radically impact education. After reading the chapter, Tom Gordon was inclined to agree and scheduled a meeting with Mark DeLonge.

Tom and Mark began looking for a system or tool that could do exactly what they wanted while remaining true to Carey’s observations. They had no luck. In late 2014 they approached Computer Information Technology professor, Jeff Straw, who created a prototype using HTML and Javascript files. They built several PLMs using the following process: Tom would select the pictures (he focused on geography) to be used in the PLMs. Mark and other staff from NMC’s Educational Media Technology department would then add arrows or other indicators to show which part of the image Tom wanted to identify. The images were added, the code adjusted, the files packaged together, and everything was put into Moodle as an “object.” This process required several NMC personnel and several weeks to create a single PLM.

We realized that this wasn’t sustainable and that we needed a PLM creation tool (PLM Generator) if we were going to do our part to “radically impact education.” Ideally, we would create a system with which a single user could create a high-quality PLM in a matter of hours. By this point, Jeff Straw had retired and John Velis became involved by giving his Computer Information Technology capstone project course the option to tackle our project. They agreed and built what we believe to be the world’s first and only* PLM Generator in Spring semester of 2016.

The system was rather “buggy” and several of the students chose to spend the summer of 2016 on an internship to continue working on the project. At the end of summer, the internship ended though one of the interns continued through fall of 2016. A new intern finished “cleaning up” during Spring of 2017. The “cleaning up” process was quite extensive and involved sorting and correcting a good deal of troublesome coding. The final project contains its own image editor, source attribution for images, a leader board and several other bells and whistles. One user can now build a high quality PLM in hours rather than weeks.

They have presented this project at the Online Learning Consortium in Orlando, Florida and begun the process of bringing faculty from other institutions into the site to build PLMs. So far people from nearly a dozen schools have signed up to build PLMs. Tom and Mark report that they still need to clean up some of the code and fix a few bugs that exist in the administrative side so that this project can go truly global without becoming burdensome to the host institution (NMC). Any award money from LAND would be applied to these efforts. The site is located at plmlearning.org. PLM generator at OLC in Orlando and signing up people from nearly a dozen schools across the country to build PLMs.

Note: This is a beta-testing environment and may require patience at times.